testing

Articles

Person looking at a bar graph for information Information Loss in Software Testing

The higher you climb in the organization, the less information you get: An executive might only see red, yellow, and green for a project. Any time different teams need to communicate complex information, there is bound to be some information loss, and maybe some information control. We just need to understand where and why that happens, and—hopefully—how we can mitigate it.

Matthew Heusser's picture Matthew Heusser
QA professionals performing continuous testing How Continuous Testing Is Done in DevOps

DevOps does speed up your processes and make them more efficient, but companies must focus on quality as well as speed. QA should not live outside the DevOps environment; it should be a fundamental part. If your DevOps ambitions have started with only the development and operations teams, it’s not too late to loop in testing. You must integrate QA into the lifecycle in order to truly achieve DevOps benefits.

Junaid Ahmed's picture Junaid Ahmed
Woman wearing a hard hat and working with a machine Blending Machine Learning and Hands-on Testing

As your QA team grows, manual testing can lose the ability to focus on likely problem areas and instead turn into an inefficient checkbox process. Using machine learning can bring back the insights of a small team of experienced testers. By defining certain scenarios, machine learning can determine the probability that a change has a serious defect, so you can evaluate risk and know where to focus your efforts.

James Farrier's picture James Farrier
Car dashboard with various meters and dials 5 Key Elements for Designing a Successful Dashboard

When you’re designing a dashboard to track and display metrics, it is important to consider the needs and expectations of the users of the dashboard and the information that is available. There are several aspects to consider when creating a new dashboard in order to make it a useful tool. For a mnemonic device to help you easily remember the qualities that make a good dashboard, just remember the acronym “VITAL.”

Nels Hoenig's picture Nels Hoenig
Cards and chips at a casino Risk Coverage: A New Currency for Testing

In the era of agile and DevOps, release decisions need to be made rapidly—preferably, even automatically and instantaneously. Test results that focus solely on the number of test cases leave you with a huge blind spot. If you want fast, accurate assessments of the risks associated with promoting the latest release candidate to production, you need a new currency in testing: Risk coverage needs to replace test coverage.

Wolfgang Platz's picture Wolfgang Platz
2020 letters and confetti 7 Agile Testing Trends to Watch for in 2020

With 2020 upon us, software development firms seeking to increase their agility are focusing more and more on aligning their testing approach with agile principles. Let’s look at seven of the key agile testing trends that will impact organizations most this year.

Nick Karlsson's picture Nick Karlsson
Person holding sparkler with New Year's fireworks in the background Top 10 StickyMinds Articles of 2019

Teams everywhere are looking to speed up testing without sacrificing quality, so once again, some of the top articles last year were about continuous integration, machine learning, and—of course—how to best implement and use test automation. But readers were also interested in what they shouldn't be doing, with two high-ranking articles about test practices we should stop and a tool you may be misusing.

Beth Romanik's picture Beth Romanik
Laptop screen showing test data analytics Applying Data Analytics to Test Automation

Testers gather lots of metrics about defect count, test case execution classification, and test velocity—but this information doesn't necessarily answer questions around product quality or how much money test efforts have saved. Testers can better deliver business value by combining test automation with regression analysis, and using visual analytics tools to process the data and see what patterns emerge.

Harsh Vardhan's picture Harsh Vardhan
Test data shown on a dashboard Improving Test Data Collection and Management

There is much published about the data we generate to assess product quality. There is less discussion about the data testers generate for our own use that can help us improve our work—and even less is said about recommended practices for data collection. Test data collection, management, and use all call for upfront planning and ongoing maintenance. Here's how testers can improve these practices.

Michael Stahl's picture Michael Stahl
Computer showing data analysis Rookie Mistakes in Data Analytics

It's easy to make simple mistakes in data analysis. But these little mistakes can result in rework, errors, and—in the worst case—incorrect conclusions that lead you down the wrong path. Making small process changes can help you steer clear of these mistakes and end up having a real impact, both in the amount of time you spend and in your results. Here are some tips for avoiding rookie mistakes in data analytics.

Nels Hoenig's picture Nels Hoenig

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